Global estimates of transmission intensity and short-term forecasts during the COVID-19 pandemic
Challenges, impacts and implications for the future
https://epiforecasts.io
The answer to the question is not always obvious
30 January,2020
2 March, 2020
August 2020
Generative Bayesian model
\[ \begin{align} \textrm{New infections}~I(t) & = R_t \sum_{\tau} g_{\tau} I_{t-\tau}\\ \textrm{Reproduction number}~R(t) & = R_{t-1} \exp(\textrm{GP})\\ \textrm{Delayed reporting}~D(t) & = \sum_\tau \xi_\tau I_{t-\tau} \\ \textrm{Observations}~C(t) & = \mathrm{NegBin}(D_t \omega_{(t \textrm{mod} 7)}, \phi) \end{align} \]
R package for \(R_t\) estimation and forecasting
R package for (sub-)national data
Subnational estimates
Daily estimates stored on github
Challenge #1: Methodology
Originally used methodology that ignored delays.
Challenge #2: Lack of local context
Challenge #3: Communication
Challenge #4: Multiplication of effort
Challenge #5: Capacity
Impact #1: Use by other researchers
Impact #2: Use by ourselves
Davies et al., Science, 2021 Abbott et al., medRxiv, 2021 Sheratt et al., Proc Roy Soc B, 2021
Tools as route towards localised work
Tool development for epidemic preparedness
